Growth Form Patterns Across Palm Subfamilies

Relationship between taxonomic classification and physical growth characteristics

Exploring growth patterns and morphological diversity across palm tree subfamilies using the PalmTraits 1.0 database, revealing how evolutionary history shapes physical characteristics.

Figure 1: Alluvial diagram showing growth form patterns across palm subfamilies. The visualization flows from left to right, connecting palm subfamilies (Arecoideae, Calamoideae, Ceroxyloideae, and Coryphoideae) to growth forms (Erect, Non-erect, and both) to stem types (Solitary Stem, Clustered Stems, and both). The diagram reveals distinctive patterns: Arecoideae palms show diverse growth habits, Calamoideae are predominantly erect with clustered stems, Ceroxyloideae show a mix of growth forms, and Coryphoideae are mainly non-erect with solitary stems. The flow width represents the percentage of species with each characteristic.

Steps to Create this Graphic

1. Load Packages & Setup

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
    tidyverse,      # Easily Install and Load the 'Tidyverse'
    ggtext,         # Improved Text Rendering Support for 'ggplot2'
    showtext,       # Using Fonts More Easily in R Graphs
    janitor,        # Simple Tools for Examining and Cleaning Dirty Data
    skimr,          # Compact and Flexible Summaries of Data
    scales,         # Scale Functions for Visualization
    glue,           # Interpreted String Literals
    here,           # A Simpler Way to Find Your Files
    camcorder,      # Record Your Plot History 
    ggalluvial,     # Alluvial Plots in 'ggplot2'
    MetBrewer      # Color Palettes Inspired by Works at the Metropolitan Museum of Art
    )
})

### |- figure size ----
gg_record(
    dir    = here::here("temp_plots"),
    device = "png",
    width  =  10,
    height =  10,
    units  = "in",
    dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))

2. Read in the Data

tt <- tidytuesdayR::tt_load(2025, week = 11) 

palmtrees_raw <- tt$palmtrees |> clean_names()

tidytuesdayR::readme(tt)
rm(tt)

3. Examine the Data

glimpse(palmtrees_raw)
skim(palmtrees_raw)

4. Tidy Data

### |-  tidy data ----
growth_form_data <- palmtrees_raw |>
    filter(!is.na(erect), !is.na(stem_solitary), !is.na(palm_subfamily)) |>
    count(palm_subfamily, erect, stem_solitary) |>
    group_by(palm_subfamily) |>
    filter(sum(n) > 20) |>  
    mutate(percentage = n / sum(n) * 100) |> 
    ungroup() |>
    mutate(
        erect_label = case_when(
            erect == "erect" ~ "Erect",
            erect == "non-erect" ~ "Non-erect",
            TRUE ~ as.character(erect)
        ),
        stem_solitary_label = case_when(
            stem_solitary == "solitary" ~ "Solitary Stem",
            stem_solitary == "non-solitary" ~ "Clustered Stems",
            TRUE ~ as.character(stem_solitary)
        ),
        palm_subfamily = str_to_title(palm_subfamily)
    ) 

5. Visualization Parameters

### |-  plot aesthetics ----
colors <- get_theme_colors(
    palette = MetBrewer::met.brewer(
        name = "Kandinsky",
        n = 4,
        type = 'discrete')
)

### |-  titles and caption ----
title_text <- str_glue("Growth Form Patterns Across Palm Subfamilies")
subtitle_text <- str_glue("Relationship between taxonomic classification and physical growth characteristics")

# Create caption
caption_text <- create_social_caption(
    tt_year = 2025,
    tt_week = 11,
    source_text =  "{palmtrees} R package" 
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----

# Start with base theme
base_theme <- create_base_theme(colors)

# Add weekly-specific theme elements
weekly_theme <- extend_weekly_theme(
    base_theme,
    theme(
        # Text styling 
        plot.title = element_text(face = "bold", family = fonts$title, size = rel(1.14), margin = margin(b = 10)),
        plot.subtitle = element_text(family = fonts$subtitle, color = colors$text, size = rel(0.78), margin = margin(b = 20)),
        
        # Axis elements
        axis.title = element_text(color = colors$text, face = "bold", size = rel(0.8)),
        axis.text = element_text(color = colors$text, size = rel(0.7)),
        
        # Grid elements
        panel.grid.minor = element_line(color = "gray80", linewidth = 0.05),
        panel.grid.major = element_line(color = "gray80", linewidth = 0.02),
        
        # Legend elements
        legend.position = "top",
        legend.direction = "horizontal",
        legend.title = element_text(family = fonts$text, size = rel(0.8), face = "bold"),
        legend.text = element_text(family = fonts$text, size = rel(0.7)),
        
        # Plot margins 
        plot.margin = margin(t = 10, r = 10, b = 10, l = 10),
    )
)

# Set theme
theme_set(weekly_theme)

6. Plot

### |-  Plot  ----
p <- ggplot(
    data = growth_form_data,
    aes(
        y = percentage,
        axis1 = palm_subfamily,
        axis2 = erect_label,
        axis3 = stem_solitary_label
        )
    ) +
    
    # Geoms                                   # flow appearance
    geom_alluvium(aes(fill = palm_subfamily),
                  width = 0.25,
                  alpha = 0.7, 
                  knot.pos = 0.3
    ) + 
    geom_stratum(                             # strata appearance
        width = 0.35,
        fill = "gray95", 
        color = "gray40", 
        size = 0.6,
        alpha = 0.85
    ) +
    geom_text(
        stat = "stratum",
        aes(label = after_stat(stratum)),
        size = 4,
        fontface = "bold",
        color = "gray10"
    ) + 
    
    # Scales
    scale_x_discrete(
        limits = c("Subfamily", "Growth Form", "Stem Type"),
        expand = c(0.08, 0.08)
    ) + 
    scale_fill_manual(values = colors$palette) +
    coord_cartesian(clip = 'off') +
    
    # Labs
    labs(
        title = title_text,
        subtitle = subtitle_text,
        caption = caption_text,
        y = "Percentage of Species (%)",
        x = NULL
    ) +
    
    # Legend
    guides(
        fill = guide_legend(title = "Palm Subfamily: ", nrow = 1)
    ) +
    
    # Theme
    theme(
        plot.title = element_text(
            size = rel(2.2),
            family = fonts$title,
            face = "bold",
            color = colors$title,
            lineheight = 1.1,
            margin = margin(t = 5, b = 5)
        ),
        plot.subtitle = element_text(
            size = rel(1.0),
            family = fonts$subtitle,
            color = colors$subtitle,
            lineheight = 1.2,
            margin = margin(t = 5, b = 10)
        ),
        plot.caption = element_markdown(
            size   = rel(0.65),
            family = fonts$caption,
            color  = colors$caption,
            hjust  = 0.5,
            margin = margin(t = 10)
        ),
        plot.margin = margin(t = 20, r = 10, b = 20, l = 10),
    )

7. Save

### |-  plot image ----  
save_plot_patchwork(
  plot = p, 
  type = "tidytuesday", 
  year = 2025, 
  week = 11, 
  width = 10,
  height = 10
)

8. Session Info

Expand for Session Info

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] MetBrewer_0.2.0   ggalluvial_0.12.5 camcorder_0.1.0   here_1.0.1       
 [5] glue_1.8.0        scales_1.3.0      skimr_2.1.5       janitor_2.2.0    
 [9] showtext_0.9-7    showtextdb_3.0    sysfonts_0.8.9    ggtext_0.1.2     
[13] lubridate_1.9.3   forcats_1.0.0     stringr_1.5.1     dplyr_1.1.4      
[17] purrr_1.0.2       readr_2.1.5       tidyr_1.3.1       tibble_3.2.1     
[21] ggplot2_3.5.1     tidyverse_2.0.0   pacman_0.5.1     

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.1   farver_2.1.2       fastmap_1.2.0      gh_1.4.1          
 [5] digest_0.6.37      timechange_0.3.0   lifecycle_1.0.4    rsvg_2.6.1        
 [9] magrittr_2.0.3     compiler_4.4.0     rlang_1.1.4        tools_4.4.0       
[13] utf8_1.2.4         yaml_2.3.10        knitr_1.49         labeling_0.4.3    
[17] htmlwidgets_1.6.4  bit_4.5.0          curl_6.0.0         xml2_1.3.6        
[21] repr_1.1.7         tidytuesdayR_1.1.2 withr_3.0.2        grid_4.4.0        
[25] fansi_1.0.6        colorspace_2.1-1   gitcreds_0.1.2     cli_3.6.3         
[29] rmarkdown_2.29     crayon_1.5.3       generics_0.1.3     rstudioapi_0.17.1 
[33] tzdb_0.4.0         commonmark_1.9.2   parallel_4.4.0     ggplotify_0.1.2   
[37] base64enc_0.1-3    vctrs_0.6.5        yulab.utils_0.1.8  jsonlite_1.8.9    
[41] gridGraphics_0.5-1 hms_1.1.3          bit64_4.5.2        systemfonts_1.1.0 
[45] magick_2.8.5       gifski_1.32.0-1    codetools_0.2-20   stringi_1.8.4     
[49] gtable_0.3.6       munsell_0.5.1      pillar_1.9.0       rappdirs_0.3.3    
[53] htmltools_0.5.8.1  R6_2.5.1           httr2_1.0.6        rprojroot_2.0.4   
[57] vroom_1.6.5        evaluate_1.0.1     markdown_1.13      gridtext_0.1.5    
[61] snakecase_0.11.1   renv_1.0.3         Rcpp_1.0.13-1      svglite_2.1.3     
[65] xfun_0.49          fs_1.6.5           pkgconfig_2.0.3   

9. GitHub Repository

Expand for GitHub Repo

The complete code for this analysis is available in tt_2025_11.qmd.

For the full repository, click here.

10. References

Expand for References

1. Data Sources:

   • TidyTuesday 2025 Week 11: Palm Trees